Reading ArUco Markers and AprilTags
Learn how to read fiduciary markers with OpenCV and Python using a camera.
The Python code we’ll examine is designed to load an image containing ArUco markers, detect these markers, estimate their pose, and then visualize the detected markers and their pose in 3D.
We’ll discuss two versions of the same code. In the first version, we’ll read markers without using a calibrated camera. In the second version, we’ll use a calibrated camera.
Whether we need to use a calibrated camera or not depends on our specific use case.
Get hands-on with 1400+ tech skills courses.